Redrawing the US obesity landscape: Bias- corrected estimates of state-specific adult obesity prevalence

PLoS ONE

Volumn 11, Issue 3, 2016, Pages

  Ward, Zachary J ^a   Long, Michael W ^b   Resch, Stephen C ^a   Gortmaker, Steven L ^a   Cradock, Angie L ^a   Giles, Catherine ^a   Hsiao, Amber ^c   Wang, Y Claire ^c  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b GEORGE WASHINGTON UNIVERSITY   (United States)

^c Department of Medicine   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; BEHAVIORAL RISK FACTOR SURVEILLANCE SYSTEM; BODY MASS; DISEASE SEVERITY; EPIDEMIC; HUMAN; NONPARAMETRIC TEST; OBESITY; PREVALENCE; REGRESSION ANALYSIS; SELF REPORT; UNITED STATES; AGE; FEMALE; HEALTH SURVEY; INFORMATION PROCESSING; MALE; OBESITY, MORBID;

ADULT; AGE FACTORS; BEHAVIORAL RISK FACTOR SURVEILLANCE SYSTEM; BODY MASS INDEX; DATASETS AS TOPIC; FEMALE; HUMANS; MALE; OBESITY; OBESITY, MORBID; PREVALENCE; PUBLIC HEALTH SURVEILLANCE; SELF REPORT; UNITED STATES;

EID: 84962525975     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0150735     Document Type: Article

References (34)

1. Johnson NB, Hayes LD, Brown K, Hoo EC, Ethier KA. CDC National Health Report: leading causes of morbidity and mortality and associated behavioral risk and protective factors - United States, 2005-2013. MMWR Surveill Summ. 2014; 63 Suppl 4:3-27.
2. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380 (9859):2224-2260. doi: 10.1016/S0140-6736(12)61766-8 PMID: 23245609
3. Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP. The spread of the obesity epidemic in the United States, 1991-1998. JAMA. 1999; 282(16):1519-1522. PMID: 10546690
4. Health Equity Resource Toolkit for State Practitioners Addressing Obesity Disparities. Centers for Disease Control and Prevention Web site. Available: http://www.cdc.gov/Obesity/Health-Equity/pdf/ toolkit.pdf.
5. Yun S, Zhu BP, Black W, Brownson RC. A comparison of national estimates of obesity prevalence from the behavioral risk factor surveillance system and the National Health and Nutrition Examination Survey. Int J Obes (Lond). 2006; 30(1):164-170.
6. Connor Gorber S, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007; 8(4):307-326. PMID: 17578381
7. About the National Health and Nutrition Examination Survey. Centers for Disease Control and Prevention Web site. Available: http://www.cdc.gov/nchs/nhanes/about-nhanes.htm.
8. Ezzati M, Martin H, Skjold S, Vander Hoorn S, Murray CJ. Trends in national and state-level obesity in the USA after correction for self-report bias: analysis of health surveys. J R Soc Med. 2006; 99(5):250-257. PMID: 16672759
9. Cawley J, Burkhauser R. Beyond BMI: The Value of More Accurate Measures of Fatness and Obesity in Social Science Research. NBER Working Paper Series. 2006;Working Paper 12291. Available: http://www.nber.org/papers/w12291.pdf.
10. Jain RB. Regression models to predict corrected weight, height and obesity prevalence from selfreported data: data from BRFSS 1999-2007. Int J Obes (Lond). 2010; 34(11):1655-1664.
11. Dwyer-Lindgren L, Freedman G, Engell RE, Fleming TD, Lim SS, Murray CJL, et al. Prevalence of physical activity and obesity in US counties, 2001-2011: a road map for action. Popul Health Metr. 2013; 11:7. doi: 10.1186/1478-7954-11-7 PMID: 23842197
12. Cawley J, Meyerhoefer C, Biener A, Hammer M, Wintfeld N. Savings in medical expenditures associated with reductions in body mass index among US adults with obesity, by diabetes status. Pharmacoeconomics. 2014; Nov 9 [Epub ahead of print].
13. Andreyeva T, Luedicke J, Wang YC. State-level estimates of obesity-attributable costs of absenteeism. J Occup Environ Med. 2014; 56(11):1120-1127. doi: 10.1097/JOM.0000000000000298 PMID: 25376405
14. D'Orazio M. Statistical Matching and Imputation of Survey Data with StatMatch. StatMatch R package vignette. 2014. Available: http://cran.r-project.org/web/packages/StatMatch/vignettes/Statistical- Matching-with-StatMatch.pdf.
15. D'Orazio M, Di Zio M, Scanu M. Statistical matching: theory and practice. Chichester, England; Hoboken, NJ: Wiley; 2006.
16. Vantaggi B. Statistical matching of multiple sources: a look through coherence. Int J Approx Reason. 2008; 49:701-711.
17. Gavin NI. An application of statistical matching with the survey of income and education and the 1976 Health Interview Survey. Health Serv Res. 1985; 20(2):183-198. PMID: 3159709
18. Kruppe T, Lang J. Labour market effects of retraining for the unemployed: the role of occupations. IAB Discussion Paper. 2014. Available: http://doku.iab.de/discussionpapers/2014/dp2014.pdf.
19. Müller K, Axhausen KW. Using survey calibration and statistical matching to reweight and distribute activity schedules. Transportation Research Board Annual Meeting 2014. 2014; Washington DC.
20. Masterson T. Quality of statistical match and employment simulations used in the estimation of the Levy Institute Measure of Time and Income Poverty (LIMTIP) for South Korea, 2009. Levy Economics Institute Working Paper Collection. 2014; Working Paper No. 793. Available: http://www.levyinstitute. org/pubs/wp-793.pdf.
21. Scullion JJ, Vogt KA, Sienkiewicz A, Gmur SJ, Trujillo C. Assessing the influence of land-cover change and conflicting land-use authorizations on ecosystem conversion on the forest frontier of Madre de Dios, Peru. Biol Conserv. 2014; 171:247-258.
22. About the Behavioral Risk Factor Surveillance System (BRFSS). Centers for Disease Control and Prevention Web site. Available: http://www.cdc.gov/brfss/about/about-brfss.htm.
23. When and how to construct weights when combining survey cycles. Centers for Disease Control and Prevention Web site. Available: http://www.cdc.gov/nchs/tutorials/NHANES/SurveyDesign/Weighting/ Task2.htm.
24. Andridge RR, Little RJ. A review of hot deck imputation for survey non-response. Int Stat Rev. 2010; 78 (1):40-64. PMID: 21743766
25. Silverman B, Young G. The bootstrap: to smooth or not to smooth? Biometrika. 1987; 74(3):469-479.
26. US Health Map. Institute for Health Metrics and Evaluation Web site. Available: http://vizhub. healthdata.org/us-health-map/.
27. Hollander M, Wolfe DA, Chicken E. Nonparametric statistical methods. Hoboken, NJ: Wiley; 2014.
28. Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States, States, Counties, and Puerto Rico Commonwealth and Municipios: April 1, 2010 to July 1, 2013. 2014. U.S. Census Bureau Web site. Available: http://factfinder.census.gov/faces/tableservices/jsf/pages/ productview.xhtml?src=bkmk.
29. Obesity Prevalence Maps. Centers for Disease Control and Prevention Web site. Available: http://www. cdc.gov/obesity/data/prevalence-maps.html.
30. Adult Obesity Prevalence. Centers for Disease Control and Prevention Web site. Available: http://www. cdc.gov/obesity/data/table-adults.html.
31. Arterburn DE, Maciejewski ML, Tsevat J. Impact of morbid obesity on medical expenditures in adults. Int J Obes (Lond). 2005; 29(3):334-339.
32. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff. 2009; 28(5):822-831.
33. Tsai AG, Williamson DF, Glick HA. Direct medical cost of overweight and obesity in the USA: a quantitative systematic review. Obes Rev. 2011; 12(1):50-61. doi: 10.1111/j.1467-789X.2009.00708.x PMID: 20059703
34. Le A, Judd SE, Allison DB, Oza-Frank R, Affuso O, Safford MM, et al. The geographic distribution of obesity in the US and the potential regional differences in misreporting of obesity. Obesity. 2014; 22 (1):300-306. doi: 10.1002/oby.20451 PMID: 23512879